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An Air Traffic Controller(ATC) is a person responsible for the proper Take-Off and Landing of an Aircraft from the runway, and for relaying continuous vital information back and forth from Pilots. The proposed ATC will automate this entire process to reduce human-generated errors and save costs. The entire system will be made using Artificial Intelligence and will use Natural Language Processing and Artificial Neural Networks to create a human-like, but a better-prepared system. The model needed to create the ATC, can be trained on already available crucial flight data. The data must include flight take-off and landing time, along with altered time based on weather, climate and other physical factors. The back-end system of the ATC, can be then made to work on this trained model, and produce correct and calculated flight path and timings for the take-off and Landing.

With an initial focus on critical fight management systems, the committee will evaluate applications for AI usage in aviation and aerospace and will propose standards to support implementation and certification

The new Advanced Technology and Training Center (ATTC), which opened yesterday after a ribbon-cutting ceremony, will focus on breakthroughs in condition-based maintenance and the intersection of artificial intelligence (AI), robotics, and automation within that domain.

This document discusses guidelines for the development of Aircraft Systems leveraging AI capabilities, taking into account the overall aircraft operating environment and functions. This includes validation of requirements and verification of the design implementation for certification and product assurance and guidelines with the assessment of safety.

A “toolbox” approach to systematizing the application of AI tools is described. A recommended overall approach for successful application development is suggested.

However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. ...The Adoption of Digital Twins in Integrated Vehicle Health Management, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications. Click here to access the full SAE EDGETM Research Report portfolio.

In past papers we have described the design and development of a distributed version of 3T, the three-layered AI control system. In this paper we report on its efficacy in the control and management of a cascade distiller system (CDS) for wastewater recovery.

The recent emergence of powerful artificial intelligence (AI) software development tools promises to reduce the time and effort associated with transforming an expert's knowledge into the operational software system required to implement automatic shutdown avoidance. ...To conduct an evaluation of the applicability of using AI techniques for life support processes, the National Aeronautics and Space Administration (NASA) developed a prototype expert system for automated fault detection, isolation, and correction of a regenerative carbon dioxide (CO2) removal subsystem.

Proven artificial intelligence (AI) technologies such as neural networks, fuzzy logic and expert systems present an opportunity to significantly enhance current trending and diagnostic capabilities in a real-time monitoring environment.

Potential applications include: flight accident investigation under uncertainty, advanced pilot training, research into aircraft practical aerodynamics, design of automatic flight control systems, and onboard AI technologies for flight safety.

Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.

Among these, it discusses the potential role of emerging technologies such as digital intelligence, biocomposites, biomicry, generative AI, and additive manufacturing. The aim is to identify the framework of possible drivers for Design for Sustainability approaches rethinking lightweight products lifecycles and highlight the resulting challenges and future developments.

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

MIL-STD-1553, Aircraft Internal Time Division Command/Response Multiplex Data Bus, is a military standard which has become one of the basic standardization tools being used by the DOD for avionic interfaces. The standard describes the method of communication and the electrical interface requirements for devices using this standard. The 1 Mbps serial communication bus is the prime integration scheme for electronic devices in military avionics today. This paper addresses the application of the standard to military avionic integrations, describes the scope of the standard, the technical issues resolved in selecting the particular approach, and describes several military avionic examples using the standard.

The exploration of substantial money-saving areas of suitable usage for ECM (Electrochemical Metallizing) on aircraft components which are not in the purview of the original equipment manufacturer. The focus of the paper is upon the less spectacular maintenance opportunities rather than the much discussed repair of landing gear and engine components, all of which are strictly controlled by manufacturer's specifications because of safety considerations. Non-critical parts only require documented engineering specifications which are controlled by internal corporate engineering management. Our objective is to present areas of cost savings available to maintenance departments which have frequently been overlooked in the past. The perceived need is for some presentation of examples of applications which can be found in the normal day-to-day operations of aircraft maintenance activities so that similar opportunities may be identified and acted upon.

The Raytheon Company is testing a new artificial intelligence (AI) tool developed to help determine when the multi-mode radar installed on U.S. Air Force CV-22 tiltrotor aircraft is in need of service.

Lettuce (Lactuca sativa var. Youmaicai) was cultivated at higher atmospheric CO2 concentration gradients (0.05∼2.0%), and then some parameters such as comprehensive evaluation of plant growing states, rates of photosynthesis and transpiration were carried out. There were some positive effects of elevated CO2 (0.1% to 1.0%) on the average rates of photosynthesis and transpiration of the collective lettuce leaves and the contents of chlorophyll and carotenoid, but excessive CO2 (1.5% and 2.0%) weakened the effects, and even had some negative impacts; average shoot height and leaf area of lettuce plants treated at 0.1%∼2.0% CO2 all increased, but the numbers of leaves reduced; The contents of nitrogen, potassium and vitamin C in plants decreased, but phosphorus content rose and microelement contents had no obvious change in various CO2 treatments.

This document does not prescribe specific technologies or methodologies but rather provides guidelines applicable to a range of prognostic tools, from traditional physics-based models to advanced Artificial Intelligence (AI) / Machine-Learning (ML) based algorithms. It is designed to be adaptable and generic, accommodating the evolving nature of prognostic technologies in aviation maintenance.

The paper deals with some aspects of the KOH electrolysis process, with the water electrolysis system technical data obtained on the MIR space station presented, alkali electrolysis problems are discussed with trends of electrolysis system development, some test results of solid polymer electrolyzers developed at NIICHIMMASH are presented.

Major improvements in gas-turbine engine life management and diagnostics can be achieved using artificial intelligence. More effective use of data collected in flight will be possible, post flight maintenance will be expedited, and unnecessary engine removals eliminated. Most importantly, real-time measurement of life consumption would enable the safe life of fracture critical components to be fully used before their retirement. A comprehensive on-board life measurement and diagnostics system for gas-turbine engines is necessary to support probabilistic design and life prediction methodologies for gas turbine engines and the introduction of two-level maintenance in the Air Force.